Genetic Analysis System Segmentation for Personalized Health
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Solution Overview
Problem
Current methods lack an efficient and personalized approach to assessing and utilizing genomic information for individualized medical and health decisions, particularly in correlating genotypes with phenotypes to predict disease susceptibility and treatment responses.
Innovation Solution
A method and system for generating and updating phenotype profiles based on genomic profiles by applying rules that correlate genotypes with phenotypes, using genetic samples to determine individual genotype correlations, and providing secure reporting to healthcare managers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If genomic information is collected and analyzed for personalized health assessments, then individualized medical decision-making capability is improved, but system complexity and data processing requirements increase
Solution Approach 1:
The system segments genomic analysis into distinct functional modules: sample collection, genomic profile generation, database querying for genotype-phenotype correlations, and result reporting. Each module handles specific tasks independently, reducing overall system complexity while enabling personalized assessments through coordinated operation of these segmented components.
Solution Approach 2:
A centralized database of genotype-phenotype correlations serves as an intermediary between raw genomic data and personalized health interpretations. This mediator layer simplifies the complexity by pre-storing established correlations, allowing the system to query and apply known relationships without重新 analyzing complex genomic data each time a personalized assessment is needed.
2Measurement precision
If a comprehensive database of genotype correlations is maintained and continuously updated, then accuracy of phenotype predictions is improved, but data management complexity and storage requirements increase
Solution Approach 1:
The system performs preliminary actions by pre-collecting and storing genotype-phenotype correlation data in a structured database before actual personalized assessments are conducted. This advance preparation organizes complex genomic relationships into queryable formats, improving prediction accuracy when assessments are performed while avoiding the need to process raw genomic data in real-time.
Solution Approach 2:
Instead of storing and processing complete genomic sequences for every individual assessment, the system creates and stores simplified correlation representations (genotype-phenotype relationships) that capture essential predictive information. This copying approach maintains prediction accuracy while significantly reducing data storage requirements compared to storing full genomic datasets.
3Adaptability or versatility
If genomic profiles are continuously updated and re-analyzed as new correlations become known, then personalization and currency of health information is improved, but processing time and computational resources increase
Solution Approach 1:
The system maintains continuous usefulness by implementing an update mechanism that periodically incorporates new genotype-phenotype correlations into the database as they become available through research. This continuous action ensures personalized assessments remain current without requiring complete re-analysis of individual genomic profiles, thus maintaining adaptability while controlling processing time.
Solution Approach 2:
The system employs feedback mechanisms where new scientific correlations are fed back into the database, which then updates individual genotype correlation profiles. This feedback loop ensures continuous improvement of personalization accuracy over time while using efficient update protocols that minimize processing time compared to complete re-assessments.
Data Source
AI summary
The present invention provides methods of determining a Genetic Composite Index score by assessing the association between an individual's genotype and at least one disease or condition. The assessment comprises comparing an individual's genomic profile with a database of medically relevant genetic variations that have been established to associate with at least one disease or condition.